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Nat Commun. 2017 Aug 29;8(1):382. doi: 10.1038/s41467-017-00443-5.

Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes.

Author information

1
Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA. suganthi.bala@regeneron.com.
2
Molecular Biophysics and Biochemistry Department, Yale University, New Haven, CT, 06520, USA. suganthi.bala@regeneron.com.
3
Regeneron Genetics Center, Tarrytown, NY, 10591, USA. suganthi.bala@regeneron.com.
4
Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA.
5
Bina Technologies, Part of Roche Sequencing, Belmont, CA, 94002, USA.
6
Molecular Biophysics and Biochemistry Department, Yale University, New Haven, CT, 06520, USA.
7
Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, 02114, USA.
8
Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, 02142, USA.
9
Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA. mark@gersteinlab.org.
10
Molecular Biophysics and Biochemistry Department, Yale University, New Haven, CT, 06520, USA. mark@gersteinlab.org.
11
Department of Computer Science, Yale University, New Haven, CT, 06520, USA. mark@gersteinlab.org.

Abstract

Variants predicted to result in the loss of function of human genes have attracted interest because of their clinical impact and surprising prevalence in healthy individuals. Here, we present ALoFT (annotation of loss-of-function transcripts), a method to annotate and predict the disease-causing potential of loss-of-function variants. Using data from Mendelian disease-gene discovery projects, we show that ALoFT can distinguish between loss-of-function variants that are deleterious as heterozygotes and those causing disease only in the homozygous state. Investigation of variants discovered in healthy populations suggests that each individual carries at least two heterozygous premature stop alleles that could potentially lead to disease if present as homozygotes. When applied to de novo putative loss-of-function variants in autism-affected families, ALoFT distinguishes between deleterious variants in patients and benign variants in unaffected siblings. Finally, analysis of somatic variants in >6500 cancer exomes shows that putative loss-of-function variants predicted to be deleterious by ALoFT are enriched in known driver genes.Variants causing loss of function (LoF) of human genes have clinical implications. Here, the authors present a method to predict disease-causing potential of LoF variants, ALoFT (annotation of Loss-of-Function Transcripts) and show its application to interpreting LoF variants in different contexts.

PMID:
28851873
PMCID:
PMC5575292
DOI:
10.1038/s41467-017-00443-5
[Indexed for MEDLINE]
Free PMC Article

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